Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_networkanalysis”.

  FT_NETWORKANALYSIS computes various network graph measures from
  between-channel or between source-level EEG/MEG signals. This function
  acts as a wrapper aroun the network metrics implemented in the brain
  connectivity toolbox developed by Olaf Sporns and colleagues.
  Use as
    stat = ft_networkanalysis(cfg, data)
  where the first input argument is a configuration structure (see below)
  and the second argument is the output of FT_CONNECTIVITYANALYSIS.
  At present the input data should be channel-level data with dimord
  'chan_chan(_freq)(_time)' or source data with dimord
  The configuration structure has to contain
    cfg.method    = string, specifying the graph measure that will be
                    computed. See below for the list of supported measures.
    cfg.parameter = string specifying the bivariate parameter in the data
                    for which the graph measure will be computed.
  Supported methods are
    betweenness,      betweenness centrality (nodes)
    charpath,         characteristic path length, needs distance matrix as
    clustering_coef,  clustering coefficient
    edge_betweenness, betweenness centrality (edges)
  To facilitate data-handling and distributed computing you can use
    cfg.inputfile   =  ...
  	cfg.outputfile  =  ...
  If you specify one of these (or both) the input data will be read from a
  *.mat file on disk and/or the output data will be written to a *.mat
  file. These mat files should contain only a single variable,
  corresponding with the input/output structure.